rsvp
trial_type object/animal object/animal, bird object/animal, insect object/body part object/clothing object/container object/container, kitchen utensil object/container, vehicle object/decoration object/electronic device object/food object/food, beverage object/food, dessert object/food, vegetable object/fruit object/furniture object/kitchen appliance object/kitchen utensil object/musical instrument object/plant object/sports equipment object/sports equipment, weapon object/tool object/toy object/vegetable object/vehicle object/vehicle, weapon object/weapon
subject
01 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
02 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
03 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
04 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
05 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
06 840 172 93 192 554 503 20 214 160 13 687 92 54 7 307 166 39 60 196 218 82 6 251 129 130 148 7 99
07 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
08 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
09 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
10 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
11 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
12 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
13 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
14 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
15 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
16 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
17 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
18 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
19 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
20 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
21 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
22 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
23 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
24 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
25 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
26 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
27 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
28 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
29 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
30 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
31 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
32 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
33 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
34 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
35 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
36 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
37 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
38 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
39 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
40 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
41 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
42 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
43 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
44 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
45 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
46 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
47 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
48 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
49 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
50 1500 312 168 348 996 900 36 384 288 24 1236 168 96 12 564 300 72 108 360 396 144 12 456 228 228 264 12 180
Time course (EEG)
Global field power
Time course (EEG)
Global field power
Time course (EEG)
Global field power
Full-epochs Decoding
Based on N=50 subjects. Each dot represents the mean cross-validation score for a single subject. The dashed line is expected chance performance.
Decoding performance over time
Based on N=50 subjects. Standard error and confidence interval of the mean were bootstrapped with 5000 resamples. CI must not be used for statistical inference here, as it is not corrected for multiple testing. Time periods with decoding performance significantly above chance, if any, were derived with a one-tailed cluster-based permutation test (-1 permutations) and are highlighted in yellow.
t-values based on decoding scores over time
Observed t-values. Time points with t-values > 1.677 were used to form clusters.
Decoding performance over time
Based on N=50 subjects. Standard error and confidence interval of the mean were bootstrapped with 5000 resamples. CI must not be used for statistical inference here, as it is not corrected for multiple testing. Time periods with decoding performance significantly above chance, if any, were derived with a one-tailed cluster-based permutation test (9999 permutations) and are highlighted in yellow.
t-values based on decoding scores over time
Observed t-values. Time points with t-values > 1.677 were used to form clusters.
Decoding performance over time
Based on N=50 subjects. Standard error and confidence interval of the mean were bootstrapped with 5000 resamples. CI must not be used for statistical inference here, as it is not corrected for multiple testing. Time periods with decoding performance significantly above chance, if any, were derived with a one-tailed cluster-based permutation test (-1 permutations) and are highlighted in yellow.
t-values based on decoding scores over time
Observed t-values. Time points with t-values > 1.677 were used to form clusters.
  """Configuration file for the ds003825 dataset.

Set the `MNE_BIDS_STUDY_CONFIG` environment variable to
"config_ds003825" to overwrite `config.py` with the values specified
below.

Download ds003825 from OpenNeuro: https://github.com/OpenNeuroDatasets/ds003825
"""

import itertools
from mne_bids import get_entity_vals

study_name = 'ds003825'

# bids_root = f'~/mne_data/{study_name}'

bids_root = f'/storage/store2/data/{study_name}'
deriv_root = f'/storage/store2/derivatives/{study_name}/mne-bids-pipeline/'

subjects = sorted(get_entity_vals(bids_root, entity_key='subject'))
# subjects = subjects[:1]

task = 'rsvp'
interactive = False
ch_types = ['eeg']
resample_sfreq = 250.0
epochs_tmin = -0.05
epochs_tmax = 0.6
decim = 2
baseline = (None, 0)
reject = None
# reject = {'eeg': 150e-6}
conditions = ["animal", "food", "body part"]
contrasts = list(itertools.combinations(conditions, 2))
decode = True

# not all runs have the same number of channels
# exclude_subjects = ['002', '003', '004', '005', '018', '019']

# event_repeated = "drop"
run_source_estimation = False

N_JOBS = 20
# N_JOBS = 1

on_error = "debug"

# memory_location = False


  Platform:         Linux-4.15.0-136-generic-x86_64-with-glibc2.27
Python:           3.9.9 | packaged by conda-forge | (main, Dec 20 2021, 02:41:03)  [GCC 9.4.0]
Executable:       /data/parietal/store/work/agramfor/mambaforge/bin/python3.9
CPU:              x86_64: 88 cores
Memory:           503.8 GB

mne:              1.2.dev0
numpy:            1.21.6 {MKL 2022.0-Product with 1 thread}
scipy:            1.8.1
matplotlib:       3.4.3 {backend=agg}

sklearn:          1.1.2
numba:            0.55.1
nibabel:          3.2.1
nilearn:          Not found
dipy:             Not found
openmeeg:         Not found
cupy:             Not found
pandas:           1.3.3
pyvista:          0.32.1 {OpenGL could not be initialized}
pyvistaqt:        0.5.0
ipyvtklink:       Not found
vtk:              9.1.0
qtpy:             1.11.2 {PyQt5=5.12.9}
ipympl:           Not found
pyqtgraph:        Not found
pooch:            v1.6.0

mne_bids:         0.12.dev0
mne_nirs:         Not found
mne_features:     Not found
mne_qt_browser:   Not found
mne_connectivity: Not found
mne_icalabel:     Not found